Health care researchers have long sought to harness the power of computing to design molecules that bind to specific receptors and can be used as targeted treatments for diseases. Even with the increasing sophistication of artificial intelligence, however, this technological promise has yet to be realized.

Junmei Wang, professor of pharmaceutical sciences in the School of Pharmacy, is tackling the problem from a different perspective.

In a paper published Oct. 28 in the journal Science Advances, Wang outlined Full-Spectrum Generative Lead Discovery (FSGLD), a novel, practical and reusable framework that takes advantage of generative AI to screen for existing compounds with potential for therapeutic development.